Breast cancer is the second most common type of cancer in the world. It is estimated that 29.7% of new cases diagnosed in Brazil occur in any structures of the breasts. However, the disease has a good prognosis if detected early. Thus, the development of new technologies to help doctors to provide an accurate diagnosis is indispensable. The goal of this work is to develop a new method to automate parts of computer-aided diagnosis systems, performing the unsupervised segmentation of the Region of Interest (ROI) of infrared breast images acquired in lateral view. The segmentation proposed in this paper consists of three stages. The first stage pre-processes the infrared images of the lateral region of breasts. Later, features are extracted from a descriptor based on Histogram of Oriented Gradients (HOG). Concluding, a Machine Learning algorithm is used to perform the segmentation of the sample. The current method obtained an average of 89.9% accuracy and 94.3% specificity in our experiments, which is promising compared to other works.
In addition to the increase in the number of pods produced, a well-conducted pollination also contributes to an increase in the number of grains per pod, improves the quality of the grains and seeds, and renders the grain ripening more uniform, thus, increasing the production at harvest. The objective of the present study was to quantify the benefits of flower-visiting insects in soybean production. The experiment was conducted with two soybean cultivars, one Bt and one non-Bt. During the flowering period, 150 plants of each cultivar were randomly selected, yielding 25 replicates (three plants per replicate) with free access to flower visitors, and another 25 replicates (also with three plants per replicate) that flower visitors could not access. During the flowering period, 549 specimens of flower-visiting insects were found in both cultivars, divided into eight orders, 30 families, and 92 species. The most abundant species were Apis mellifera (Linnaeus) (Hymenoptera: Apidae), Musca sp.1 (Linnaeus) (Diptera: Muscidae), and Lagria villosa (Fabricius) (Coleoptera: Tenebrionidae). In the treatment with flower visitors, grain weight increased by 84.22% in Bt cultivar and by 202.52% in non-Bt cultivar, compared with the area without the presence of flower visitors. The increase in the number of pods in Bt and non-Bt cultivars was 45.72% and 101.25% respectively, in the area open to flower visitors. The high increase in grain yield and number of pods observed in the area with free access to pollinator insects emphasizes the high importance of the pollination service performed by flower visitors to the soybean crop.
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